Oh, an empty article!

Today,
science & R&D social media channels have become just as cluttered as consumer
social media channels. For academic researchers, trying to get the word out on
your research paper has come to parallel digital and online marketing. It’s as
if communicating research main points effectively wasn’t hard enough. Now, even
trying to stay afloat on Twitter—much less going viral—is a challenge.

This is where data
visualizations come in to play. Visualized data, such as
charts, infographics, and interactive figures can represent extensive amounts
of complicated data more coherently. It's significantly
faster to analyze information in graphical format (versus in spreadsheets).
Consequently, scientists, government bodies, and businesses are able to
spot correlations, patterns, trends, outliers, etc. with greater ease.

Data
visualization also makes communication possible, effective, and interesting.Getting
over the subject-specific learning curve (e.g. jargon) often makes sharing
findings to the general public hard--even with other researchers!
Using visually impactful representations of data gets the message across
quickly, engages new audiences, encourages sharing and visibility,
and opens the floor to new research opportunities. Click
here to read about How the Scientific Community Reacts to Newly Submitted
Preprints.

According
to Buffer, content with visuals get 94% more total views and visual content is more than 40X more likely to get shared on
social media than other types of content. In fact, infographics are
liked and shared on social media 3X more than other any other type of content.
(MassPlanner) So here are a few common types of data visualizations
to help the writer to explain and reader to explore large quantities of data.

Common Types of Infographics

Cartograms
represent one variable–such as population or GDP– as land area or distance in a
2D illustration. The space is distorted to compare and contrast the variable
across many categories. This cartogram by South
China Morning Post, represents 23 languages (out of 7,102 known languages
alive today) spoken by 4.1 billion (out of total 7.4 billion) in the world.